# Data Analysis with Python Projects - Demographic Data Analyzer

### Tell us what’s happening:

Describe your issue in detail here.
i was doing projects for the data analysis but on replit for my first project it says numpy named module not available i tried installing its package from packages but the issue didnt resolve. i tried the second project it says sh1 : use not found.
both my code are running on my jupiter notebook.

import pandas as pd

def calculate_demographic_data(print_data=True):

``````# How many of each race are represented in this dataset? This should be a Pandas series with race names as the index labels.
race_count = df["race"].value_counts()

# What is the average age of men?
average_age_men = df[df["sex"] == "Male"]["age"].mean()

# What is the percentage of people who have a Bachelor's degree?
percentage_bachelors = (df["education"] == "Bachelors").mean() * 100

# What percentage of people with advanced education (`Bachelors`, `Masters`, or `Doctorate`) make more than 50K?
# What percentage of people without advanced education make more than 50K?

# with and without `Bachelors`, `Masters`, or `Doctorate`
higher_education = df[df["education"].isin(["Bachelors", "Masters", "Doctorate")]
lower_education = df[~df["education"].isin(["Bachelors", "Masters", "Doctorate"])]

# percentage with salary >50K
higher_education_rich = (higher_education["salary"] == ">50K").mean() * 100
lower_education_rich = (lower_education["salary"] == ">50K").mean() * 100

# What is the minimum number of hours a person works per week (hours-per-week feature)?
min_work_hours = df["hours-per-week"].min()

# What percentage of the people who work the minimum number of hours per week have a salary of >50K?
num_min_workers = df[df["hours-per-week"] == min_work_hours]
rich_percentage = (num_min_workers["salary"] == ">50K").mean() * 100

# What country has the highest percentage of people that earn >50K?
highest_earning_country_stats = df[df["salary"] == ">50K"]["native-country"].value_counts()
highest_earning_country = highest_earning_country_stats.idxmax()
highest_earning_country_percentage = (highest_earning_country_stats.max() / df["native-country"].value_counts().max()) * 100

# Identify the most popular occupation for those who earn >50K in India.
top_IN_occupation = df[(df["native-country"] == "India") & (df["salary"] == ">50K")]["occupation"].value_counts().idxmax()

# DO NOT MODIFY BELOW THIS LINE

if print_data:
print("Number of each race:\n", race_count)
print("Average age of men:", average_age_men)
print(f"Percentage with Bachelors degrees: {percentage_bachelors}%")
print(f"Percentage with higher education that earn >50K: {higher_education_rich}%")
print(f"Percentage without higher education that earn >50K: {lower_education_rich}%")
print(f"Min work time: {min_work_hours} hours/week")
print(f"Percentage of rich among those who work fewest hours: {rich_percentage}%")
print("Country with highest percentage of rich:", highest_earning_country)
print(f"Highest percentage of rich people in country: {highest_earning_country_percentage}%")
print("Top occupations in India:", top_IN_occupation)

return {
'race_count': race_count,
'average_age_men': average_age_men,
'percentage_bachelors': percentage_bachelors,
'higher_education_rich': higher_education_rich,
'lower_education_rich': lower_education_rich,
'min_work_hours': min_work_hours,
'rich_percentage': rich_percentage,
'highest_earning_country': highest_earning_country,
'highest_earning_country_percentage': highest_earning_country_percentage,
'top_IN_occupation': top_IN_occupation
}
``````

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### Challenge Information:

Data Analysis with Python Projects - Demographic Data Analyzer

Try `pip install numpy` at the shell command prompt.